Borrowing it
Nothing to install: this file belongs to techequitycloud/rad-modules. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/techequitycloud/rad-modules/main/.agent/skills/gke-basics/SKILL.mdgit clone --depth 1 https://github.com/techequitycloud/rad-modulesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/techequitycloud/rad-modules/gke-basics)<a href="https://agentmods.dev/skills/techequitycloud/rad-modules/gke-basics"><img src="https://agentmods.dev/badge/skills/techequitycloud/rad-modules/gke-basics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/techequitycloud/rad-modules/gke-basics"><img src="https://agentmods.dev/badge/skills/techequitycloud/rad-modules/gke-basics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00145 | $0.01206 |
| Opus 5.5 | $0.00058 | $0.00482 |
| Sonnet 5.5 | $0.00029 | $0.00241 |
| Haiku 4.5 | $0.00015 | $0.00121 |
Grade A, and why
gke-basics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to gke-basics — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Kubernetes Engine (GKE) Basics
GKE is a managed Kubernetes platform on Google Cloud for deploying, scaling, and operating containerized applications. This skill defaults to the golden path Autopilot configuration — see gke-golden-path.md for defaults, rules, and guardrails.
Quick Start
gcloud services enable container.googleapis.com
gcloud container clusters create-auto my-cluster --region=us-central1
gcloud container clusters get-credentials my-cluster --region=us-central1
kubectl create deployment hello-server \
--image=us-docker.pkg.dev/google-samples/containers/gke/hello-app:1.0
Reference Directory
Load the relevant reference based on trigger keywords. Prefer the most specific match; if ambiguous, ask the user to clarify.
| Scenario | Trigger Keywords | Reference |
|---|---|---|
| Core Concepts | Autopilot vs Standard, architecture, pricing, what is GKE | core-concepts.md |
| Golden Path & Defaults | golden path, Day-0 checklist, production defaults, cluster defaults | gke-golden-path.md |
| Cluster Creation | create cluster, new cluster, provision GKE | gke-cluster-creation.md |
| Networking | private cluster, VPC, subnet, Gateway API, DNS, ingress, egress, datapath | gke-networking.md |
| Security & IAM | Workload Identity, Secret Manager, RBAC, Binary Auth, hardening, audit, gVisor, IAM roles | gke-security.md |
| Scaling | HPA, VPA, autoscaler, autoscaling, NAP, scale pods, scale nodes | gke-scaling.md |
| Compute Classes | ComputeClass, machine family, Spot fallback, GPU node pool, node selection | gke-compute-classes.md |
| Cost | cost, savings, Spot VMs, rightsizing, CUD, optimize spend, budget | gke-cost.md |
| AI/ML Inference | inference, model serving, LLM, GPU, TPU, GIQ, vLLM | gke-inference.md |
| Upgrades | upgrade, maintenance window, release channel, patching, version | gke-upgrades.md |
| Observability | monitoring, logging, Prometheus, Grafana, metrics, alerts, dashboards | gke-observability.md |
| Multi-tenancy | multi-tenant, namespace isolation, team access, enterprise, RBAC planning | gke-multitenancy.md |
| Batch & HPC | batch, HPC, job queue, high performance, MPI, parallel | gke-batch-hpc.md |
| App Onboarding | containerize, deploy app, Dockerfile, onboard, migrate to GKE | gke-app-onboarding.md |
| Backup & DR | backup, restore, disaster recovery, CMEK | gke-backup-dr.md |
| Storage | storage, PVC, persistent volume, StorageClass, Filestore, GCS FUSE | gke-storage.md |
| Reliability | PDB, health probe, liveness, readiness, topology spread, graceful shutdown | gke-reliability.md |
| Client Libraries | client library, client-go, kubernetes python, kubernetes java, kubernetes SDK | client-library-usage.md |
| Infrastructure as Code | Terraform, IaC, HCL, infrastructure as code | iac-usage.md |
| MCP Server | MCP tools, MCP server, MCP setup | mcp-usage.md |
| CLI / Tools | gcloud, kubectl, commands, how to | cli-reference.md |
| Production Audit | production readiness, compliance, golden path check | gke-cluster-creation.md |
What ships with it
26 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/default-deny-netpol.yaml 154 B
- assets/golden-path-autopilot.yaml 3.6 KB
- assets/hpa-example.yaml 495 B
- assets/vpa-example.yaml 469 B
- assets/workload-identity-pod.yaml 793 B
- references/cli-reference.md 11 KB
- references/client-library-usage.md 2.3 KB
- references/core-concepts.md 3.0 KB
- references/gke-app-onboarding.md 4.2 KB
- references/gke-backup-dr.md 2.4 KB
- references/gke-batch-hpc.md 4.0 KB
- references/gke-cluster-creation.md 5.1 KB
- references/gke-compute-classes.md 4.6 KB
- references/gke-cost.md 5.0 KB
- references/gke-golden-path.md 4.4 KB
- references/gke-inference.md 5.3 KB
- references/gke-multitenancy.md 3.9 KB
- references/gke-networking.md 5.4 KB
- references/gke-observability.md 6.3 KB
- references/gke-reliability.md 5.0 KB
- references/gke-scaling.md 5.1 KB
- references/gke-security.md 9.4 KB
- references/gke-storage.md 4.0 KB
- references/gke-upgrades.md 4.8 KB
- references/iac-usage.md 2.1 KB
- references/mcp-usage.md 3.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 54 lines · 145 tokens per session scan A dce1ef971031
gke-basics is a skill published in the GitHub repository techequitycloud/rad-modules (2 stars, last pushed yesterday), licensed MPL-2.0. It adds 145 tokens to every session and 1,206 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to gke-basics, differing in 8 lines, and is treated as a copy.
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